Laser & Optoelectronics Progress, Volume. 60, Issue 5, 0530002(2023)

Quantitative Analysis Method of Soil Elements Combining Sensitivity Dimensionality Reduction and Support Vector Regression

Fusheng Li1,2、* and Xiaolong Zeng1,2
Author Affiliations
  • 1School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, Sichuan, China
  • 2Yangtze Delta Region Institute, University of Electronic Science and Technology of China, Huzhou 313099, Zhejiang, China
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    References(15)

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    [11] Song H S, Chen Z, Xu D C et al. Prediction of Cr, Mn, and Ni in medium and low alloy steels by GA-BP neural network combined with EDXRF technology[J]. Laser & Optoelectronics Progress, 59, 544-550(2022).

    [12] Li F S, Yang W Q, Ma Q et al. X-ray fluorescence spectroscopic analysis of trace elements in soil with an adaboost back propagation neural network and multivariate-partial least squares regression[J]. Measurement Science and Technology, 32, 105501(2021).

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    Fusheng Li, Xiaolong Zeng. Quantitative Analysis Method of Soil Elements Combining Sensitivity Dimensionality Reduction and Support Vector Regression[J]. Laser & Optoelectronics Progress, 2023, 60(5): 0530002

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    Paper Information

    Category: Spectroscopy

    Received: Dec. 15, 2021

    Accepted: Feb. 28, 2022

    Published Online: Feb. 28, 2023

    The Author Email: Fusheng Li (lifusheng@uestc.edu.cn)

    DOI:10.3788/LOP213241

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